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Variational Inference is a powerful tool in the Bayesian modeling toolkit, however, its effectiveness is determined by the expressivity of the utilized variational distributions in terms of their ability to match the true posterior distribution.
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Markov chain monte carlo and variational inference: Bridging the gap
Salimans, T., D. Kingma, and M. Welling 2015 · 2015
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Copula variational inference
Tran, D., D. Blei, and E. M. Airoldi 2015 · 2015
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Neural variational inference and learning in undirected graphical models
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Dinh, L., J. Sohl-Dickstein, and S. Bengio 2016 · 2016
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Boosting variational inference
Guo, F., X. Wang, K. Fan, T. Broderick, and D. B. Dunson 2016 · 2016
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Improved variational inference with inverse autoregressive flow
Kingma, D. P., T. Salimans, R. Jozefowicz, X. Chen, I. Sutskever, and M. Welling 2016 · 2016
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Auxiliary deep generative models
Maaløe, L., C. K. Sønderby, S. K. Sønderby, and O. Winther 2016 · 2016
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Learning in implicit generative models
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f-gan: Training generative neural samplers using variational divergence minimization
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Hierarchical variational models
Ranganath, R., D. Tran, and D. Blei 2016 · 2016
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Semi-amortized variational autoencoders
Kim, Y., S. Wiseman, A. Miller, D. Sontag, and A. Rush 2018 · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Kingma, D. P. and P. Dhariwal 2018 · 2018
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Doubly semi-implicit variational inference
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Debiasing evidence approximations: On importance-weighted autoencoders and jackknife variational inference
Nowozin, S. 2018 · 2018
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Tighter variational bounds are not necessarily better
Rainforth, T., A. R. Kosiorek, T. A. Le, C. J. Maddison, M. Igl, F. Wood, and Y. W. Teh 2018 · 2018
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On the convergence of adam and beyond
Reddi, S. J., S. Kale, and S. Kumar 2018 · 2018
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Unbiased implicit variational inference
Titsias, M. K. and F. J. Ruiz 2018 · 2018
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Semi-implicit variational inference
Yin, M. and M. Zhou 2018 · 2018
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The deep weight prior
Atanov, A., A. Ashukha, K. Struminsky, D. Vetrov, and M. Welling 2019 · 2019
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Doubly reparameterized gradient estimators for monte carlo objectives
Tucker, G., D. Lawson, S. Gu, and C. J. Maddison 2019 · 2019
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